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» On the use of spiking neural network for EEG classification
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ISCAS
2011
IEEE
278views Hardware» more  ISCAS 2011»
13 years 13 days ago
A programmable axonal propagation delay circuit for time-delay spiking neural networks
— we present an implementation of a programmable axonal propagation delay circuit which uses one first-order logdomain low-pass filter. Delays may be programmed in the 550ms rang...
Runchun Wang, Craig T. Jin, Alistair McEwan, Andr&...
IJON
2007
91views more  IJON 2007»
13 years 8 months ago
Dynamics of parameters of neurophysiological models from phenomenological EEG modeling
We investigate a recently proposed method for the analysis of oscillatory patterns in EEG data, with respect to its capacity of further quantifying processes on slower (< 1 Hz)...
E. Olbrich, Thomas Wennekers
BC
2006
105views more  BC 2006»
13 years 8 months ago
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
Cengiz Günay, Anthony S. Maida
ICES
2010
Springer
277views Hardware» more  ICES 2010»
13 years 6 months ago
An Efficient, High-Throughput Adaptive NoC Router for Large Scale Spiking Neural Network Hardware Implementations
Recently, a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an ef...
Snaider Carrillo, Jim Harkin, Liam McDaid, Sandeep...
FUIN
2008
103views more  FUIN 2008»
13 years 8 months ago
Implementing Sorting Networks with Spiking Neural P Systems
Spiking neural P systems simulate the behavior of neurons sending signals through axons. Recently, some applications concerning Boolean circuits and sorting algorithms have been pr...
Rodica Ceterchi, Alexandru Ioan Tomescu